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  <title>Description of FbReconstruct2d</title>
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<h1>FbReconstruct2d
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<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
<div class="box"><strong>Use to see how much image information is preserved in filter outputs.</strong></div>

<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
<div class="box"><strong>function I2 = FbReconstruct2d( I, FB, patch ) </strong></div>

<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
<div class="fragment"><pre class="comment"> Use to see how much image information is preserved in filter outputs.

 Reconstructs the orginal image from filter outputs (approximately). The
 filter output for a patch is given by IFR=F*P where F is the set of
 filters in matrix form, P is the patch and IFR is the filter responses at
 the center of the patch.  We want to recover P from IFR and F, this is
 underconstrained but a solution can be found using least squared.  Note
 that each recovered P will be 0 mean if no mean information is captured
 by the filter outputs.  Can apply to a single patch (interatctively
 specified), or the entire image (by keeping the central pixel from each
 patch).

 USAGE
  I2 = FbReconstruct2d( I, FB, patch )

 INPUTS
  I      - original image
  FB     - FB to apply and do reconstruction with
  patch  - reconstruct just patch or entire image

 OUTPUTS
  I2     - reconstructed image / patch

 EXAMPLE
  load trees; X=imresize(X,.5); load FbDoG.mat;
  I2 = FbReconstruct2d( X, FB, 0 );

 See also <a href="FbApply2d.html" class="code" title="function FR = FbApply2d( I, FB, shape, show )">FBAPPLY2D</a>

 Piotr's Computer Vision Matlab Toolbox      Version 2.0
 Copyright 2014 Piotr Dollar.  [pdollar-at-gmail.com]
 Licensed under the Simplified BSD License [see external/bsd.txt]</pre></div>





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